machine learning for beginners – neural networks
machine learning for beginners – neural networks 4.3 (23 ratings) Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
What you’ll learn
- being able to create your own neural networks in python
- train and evalute your neural network
- make predictions with your model
- being able to leverage scikit learn in combination with keras
- create convolutional neural networks for image recognition
What is machine learning / ai ? How to lean machine learning in practice?
There are a lot of interested people out there but many do not know where to start. The difficult question basically is how to start actually learning it?
Especially beginners might get discouraged because of statistics and math which is an integral part of machine learning. Also matrix operations in tensorflow are not considered easy peasy. None the less you do not need to be a math expert to apply machine learning. This is my third course to show you why.
Instead of telling you all the statistics and math behind the neural network and deep learning i prefer to give you a much more hands on approach. At the end of the day there’s only one thing that really counts – THE RESULT. I believe in a practical approach. That’s why the course is developed to encourage you to follow along and write the code yourself. At the end you can see your result.
By joining this course you can leverage the knowledge you acquired from my first two courses (Machine Learning for Beginners and machine learning for beginners – deep dive) and get the chance to dive into theworld of neural networks. Again this course is not for students who like to learn theory. Those